4,696 research outputs found
Robots for Exploration, Digital Preservation and Visualization of Archeological Sites
Monitoring and conservation of archaeological sites
are important activities necessary to prevent damage or to
perform restoration on cultural heritage. Standard techniques,
like mapping and digitizing, are typically used to document the
status of such sites. While these task are normally accomplished
manually by humans, this is not possible when dealing with
hard-to-access areas. For example, due to the possibility of
structural collapses, underground tunnels like catacombs are
considered highly unstable environments. Moreover, they are full
of radioactive gas radon that limits the presence of people only
for few minutes. The progress recently made in the artificial
intelligence and robotics field opened new possibilities for mobile
robots to be used in locations where humans are not allowed
to enter. The ROVINA project aims at developing autonomous
mobile robots to make faster, cheaper and safer the monitoring of
archaeological sites. ROVINA will be evaluated on the catacombs
of Priscilla (in Rome) and S. Gennaro (in Naples)
Trajectory similarity analysis in movement parameter space
This paper introduces a similarity analysis method for moving object trajectories. The proposed method assesses the similarity between a set of trajectories in a multidimensional space, whose dimensions are formed by different movement parameters (e.g. position, speed, acceleration, direction), plus time. We investigate the applicability of the proposed method in finding relative movement patterns such as coincidence and concurrence in the movement of North Atlantic hurricanes
Vision systems with the human in the loop
The emerging cognitive vision paradigm deals with vision systems that apply machine learning and automatic reasoning in order to learn from what they perceive. Cognitive vision systems can rate the relevance and consistency of newly acquired knowledge, they can adapt to their environment and thus will exhibit high robustness. This contribution presents vision systems that aim at flexibility and robustness. One is tailored for content-based image retrieval, the others are cognitive vision systems that constitute prototypes of visual active memories which evaluate, gather, and integrate contextual knowledge for visual analysis. All three systems are designed to interact with human users. After we will have discussed adaptive content-based image retrieval and object and action recognition in an office environment, the issue of assessing cognitive systems will be raised. Experiences from psychologically evaluated human-machine interactions will be reported and the promising potential of psychologically-based usability experiments will be stressed
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